Methods and Systems for Finding Connections Among Subscribers to an Email Campaign

ABSTRACT

Methods and systems to find connections among subscribers to a particular electronic mail (email) newsletter. A list of email addresses to an email campaign is representative of the subscribers to email newsletters that are sent as part of the campaign by a source. A subscriber to a particular email newsletter may receive email newsletter from other sources. A determination is made as to what other email newsletters of each subscribers of the source receive from other sources. The other email newsletters of each subscriber on the list of email addresses of a source are compared to the other subscribers on the list of email addresses. Email newsletters common to subscribers on the list of email addresses are noted. The connections between/among subscribers on the list of email addresses is determined. The weight of a connection may be determined. The connection information may be provided as a service to the source.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application claims priority to and benefit of the prior filed co-pending and commonly owned provisional applications, filed in the United States Patent and Trademark Office on Mar. 15, 2013, assigned Ser. No. 61/800,734, and entitled Methods and Systems for Making Use of a Bounce Rate, and on Mar. 15, 2013, assigned Ser. No. 61/801,043, and entitled Methods and Systems for Finding Targets for an Email Campaign. Both provisional applications are incorporated herein by reference.

FIELD OF THE INVENTION

The invention relates to communications, and particularly, relates to electronic mail, and even more particularly, relates to information that may be gleaned from data on email campaigns.

BACKGROUND

A business may send out email newsletters periodically to a list of email addresses representing subscribers or recipients who have agreed to receive the email newsletters. The business, however, may be in the dark about what may be done to expand its list of email subscribers or to better mount its email campaigns by way of advertising and marketing.

SUMMARY

Stated generally, the invention relates to finding connections among subscribers to a particular electronic mail newsletter from a source, and to finding the weight of the connections. A source of email newsletters may be interested in the connections and weighted connections among its subscribers to advance its own advertising and marketing efforts. A service provider that stores and has access to a lot of data about the source's email campaigns as well as email campaigns of other sources may provide a connection determination service that may prove to be advantageous to the source.

Other features and advantages of the invention may be more clearly understood and appreciated from a review of the following detailed description and by reference to the appended drawings and claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a table illustrating an exemplary embodiment of the invention.

FIG. 2 is a flow diagram illustrating an exemplary embodiment of the invention.

DETAILED DESCRIPTION

The invention is described herein with reference to exemplary embodiments, alternative embodiments, and drawings. The invention, however, may be embodied in many different forms and carried out in a variety of ways that are not specifically described herein. For example, the invention may be practiced without many of the specific details provided herein.

Well-known machines or processes have not been described herein in particular detail in order to avoid unnecessarily obscuring the invention. For example, reference may be made to Wood, United States Patent Publication US 2010/0153394, published Jun. 17, 2011 for information on an exemplary computer system. For information on the infrastructure of ESPs, ISPs, and spam filters see Wood, as well as Kuhlmann et al., United States Patent Publication US 2006/0026242, published Feb. 2, 2006. Both Wood and Kuhlmann et al., which are incorporated herein by reference.

There are entities that have access to a lot of information or data about email communications. By the nature of the services it provides, an email service provider (ESP) is such an entity. With regard to this invention, the term “email service provider” refers to an entity that sends emails such as email newsletters on behalf of its customers and/or that facilitates email marketing for customers. An ESP also may be referred to as an email broadcast service provider or an ESP (marketing). Even though the exemplary embodiments are described with respect to an ESP, the invention is not to be limited to ESPs.

An ESP has customers on whose behalf the ESP may conduct email campaigns. An email campaign is a service that the ESP provides a customer generally in return for payment. As part of an email campaign, the customer may provide the ESP with an email communication such as an email newsletter and a list of email addresses to which the email communication is to be sent.

Through the course of conducting many email campaigns on behalf of many customers, an ESP may store and have ready access to a vast amount of data on email campaigns. Obviously, the ESP has information on the recipients of a particular customer's email newsletter based on the list of email addresses for the recipients provided to the ESP by the customer. These recipients also may be referred to as subscribers to the customer's email newsletter.

By an ESP having a lot of customers, each of which may send an email newsletter to a lengthy list of email address of subscribers, and including some customers which may send more than one email newsletter, an ESP has a lot information on subscribers to an ESP's customer's email newsletter. The information may relate to other subscriptions held by the customer's subscribers. The customer may be unaware of this information about its own subscribers or may not have access to it, etc. For example, an ESP may have a record that a subscriber receives email newsletter A from customer Z, email newsletter B from customer Y, and email newsletter C from customer X. Typically, the customers Z, Y, and X do not have that information on the subscriptions of the subscriber. Yet, that information may be valuable to the customers Z, Y, and X. The information may show a customer trends among its subscribers, and show content with which its subscribers are engaged. The customer may use this information to better target its customers or proposed new customers, etc.

Reference is made to FIG. 1, which is an exemplary table 10 with three rows 12, 14, 16. Each row includes an email address for a subscriber to a customer's newsletter. The table 10 also includes seven columns 18, 20, 22, 24, 26, 28. Each column relates to an email newsletter. In this example, the seven email newsletters represent the email newsletters the subscribers receive besides the email newsletter of the ESP's customer. But not all subscribers receive the same email newsletters. The table 10 includes a “1” in the square connecting a subscriber to an email newsletter that the subscriber receives. The table 10 includes a “0” in the square connecting a subscriber to an email newsletter to which the subscriber does not subscribe.

The table 10 reveals the information that Veronica and Eric share three subscriptions, and Lord Grantham and Eric share two subscriptions. The shared subscriptions may provide the ESP's customer with insight and information regarding at least between the pairs of subscribers.

Given that Veronica and Eric share more subscriptions than Lord Grantham and Eric, the customer may deduce that Veronica and Eric have a closer connection than Lord Grantham and Eric. A close connection may be said to be “weightier” or have more weight than a connection that is not as close. The table 10, however, reveals information that may need to be taken into account when considering the weight of the connections between/among the subscribers. The table 10 reveals that Veronica subscribes to all seven email newsletters. Thus, Veronica's apparent greater connection to Eric than Lord Grantham's connection to Eric may be cast into doubt, possibly because of the lack of discernment in Veronica's subscriptions to email newsletters. There may be other examples of information that may need to be taken into account when considering the connections between/among subscribers.

A method to handle instances such as Veronica's subscription to all email newsletters is by calculation of a cosine similarity. For further information on the cosine similarity calculation, please refer to http://en.wikipedia.org/wiki/cosine_similarity.

The weight or closeness of the connection between Eric and Veronica is calculated by reference to their three shared subscriptions, the square root of Eric's total connections (square root of 3), and the square root of Veronica's total connections. The formula is 3 divided by the square root of 3×the square root or 7 or 3/sqrt(21)−0.65. In other words, the closeness or weight of the connection between Veronica and Eric is 0.65. Using the same formula, the closeness or weight of the connection between Lord Grantham and Eric is 2/sqrt(9)=0.67. Despite having more subscriptions in common with Eric, Veronica's subscription to all of the email newsletters results in a finding that Lord Grantham and Eric have closer connection.

If a customer of an ESP is provided with the results of the above-described analysis and calculations with respect to all of the recipients on the customer's list(s), the customer may glean interesting information. The customer may find little pockets or communities of subscribers who are different from the rest. The customer may adjust its advertising and marketing accordingly.

FIG. 2 is a flow diagram 30 reflecting the actions described above in finding connections among subscribers to a customer's email newsletter. These actions may be carried out by an ESP as a service to its customer. In action 32, the ESP receives a list of email addresses from a customer. Each email address represents a subscriber to the email newsletter of the customer. In action 34, the ESP may use its stored data on the subscribers in the email address list to determine the other email newsletters, which the subscribers receive or subscribe to. A table may be constructed similar to the example of table 10 in FIG. 1 with rows for the email addresses and columns for the other email newsletters. For each email address, in action 36, a “1” may be marked in the square that connects to an email newsletter to which the subscriber associated with the email address subscribes. Also for each email address, in action 38, a “0” may be marked in the square that connects to an email newsletter to which the subscriber does not subscribe. In action 40, connections between/among the subscribers may be made. For example, the weight of a connection between two subscribers may be determined by using the cosine similarity mentioned above.

The construction of the table with “1”s and “0”s and the determination of the connections between/among the subscribers need not be literal. Rather, the table or its equivalent may be conducted by use of a formula, logic, etc., and/or with the aid of a computer.

Above, subscribers to one or more email newsletters were used by way of example. The analysis and calculations relating to finding connections and determining the weight of connections may be applied in other situations with other elements.

Reference again is made to the customer of an ESP and the customer's email newsletter subscribers. As noted, the customer may have thousands of subscribers for an email newsletter. Also as noted, the customer may send out more than one email newsletter. The large amount of information relating to the customer and its recipients is stored by the ESP. It may use the above analysis and calculations to detect patterns in the connections between/among subscribers and to detect communities of subscribers having closer connections with each other than other subscribers. Investigation into a community of subscribers having closer connections with each other than other subscribers may reveal that the community is made up of a type of subscriber. Information on the type of subscriber may be valuable to the customer of the ESP for advertising, marketing, etc.

The information gained from the analysis and calculations described above in connection with Table 1 may be used to create a graph of subscriber connections or distances. The graph may result in something like a network, web, or spider web where each subscriber is connected to every other subscriber at least by being a subscriber of the customer's email newsletters. Nonetheless, there may be greater or closer connection between/among some subscribers. As the weight or closeness connection between/among subscribers increases, the lines connecting the subscribers in the graph increase in thickness. Thus, the graph displays the weight of connections among subscribers of a customer. Advantageously, the graph's spider web display may be more easily read and evaluated than using the analysis and calculations alone.

The determination of connections between/among a customer's subscribers and/or the determination of the weights of the respective connections may provide an ESP with an opportunity to render another service to its customer. This service relates to providing the customer with information on the email newsletters the customer's subscribers receive other than the customer's own email newsletters.

For example, referring to table 10 in FIG. 1 again, the ESP may offer to provide the customer with the information that Eric Taylor subscribes to TED Talks, wwo!, and Goop, that Veronica Mars subscribes to those three email newsletters plus Gawker, Smashing Magazine, The Economist, and Ars Technica, and that Lord Grantham subscribes to woot! and Goop. The information about the other newsletter to which its subscribers subscribe may aid the ESP's customer in its advertising and marketing efforts.

There is another advantage, however, for the ESP's customer to receive information about other email newsletters the customer's subscribers receive. That advantage is that the customer may look to form a business relationship with one or more of the other email newsletter publishers. The customer may contact one or more of the publishers with the idea of linking to each other and growing their respective email lists organically.

A customer may authorize its ESP to share information about its lists of email addresses and/or the email newsletters those respective lists receive. There may be situations, however, where a customer of an ESP does not want its list of email addresses to be used to reveal the email that the customer sends to that list of email addresses. Thus, this service may allow a customer to designate an email address list and/or the email transmitted to the list to be “private” and not subject to further distribution. For example, a customer who is sending an internal company newsletter, a wedding invitation, or a one-time prize notification may not want the emails containing such information further distributed.

CONCLUSION

The above-described embodiments have been provided by way of example and the present invention is not limited to these examples. Multiple variation and modifications to the disclosed embodiments will occur, to the extent not mutually exclusive, to those skilled in the art upon consideration of the foregoing description. Such variations and modifications, however, may fall well within the scope of the invention as set forth in the following claims. 

1. A method to find connections among subscribers to a particular electronic mail (email) newsletter, comprising: receive a list of email addresses with each email address representing a subscriber to the particular email newsletter; determine other email newsletters to which the subscribers subscribe; determine total number of the other email newsletters to which each subscriber subscribes; determine which of the other email newsletters are common to each pair of the subscribers; determine number of the other email newsletters common to the each pair of the subscribers; based on the number of the other email newsletters in common among to the each pair of the subscribers, the total number of the other email newsletters to which a first of the each pair of the subscribers subscribes, and the total number of the other email newsletters to which a second of the each pair of the subscribers subscribes, determine the connections among the respective pairs of the subscribers to the particular email newsletter, determine a weightiest connection of the connections among the respective pairs of the subscribers; determine weightiest connection email newsletters from the other email newsletters with the weightiest connection email newsletters being associated with the weightiest connection of the connections; selectively display a page of each of the weightiest connection email newsletters.
 2. (canceled)
 3. The method of claim 1, wherein determining the connections among the subscribers to the particular email newsletters comprises using a cosine similarity function.
 4. (canceled)
 5. The method of claim 1, further comprising: prior to the selectively display of the page of each of the weightiest connection email newsletters, determining whether each of the weightiest connection email newsletters is public; and only selectively displaying the page of each of the public weightiest connection email newsletters.
 6. The method of claim 1, wherein the other email newsletters to which the subscribers subscribe comprise other public email newsletters.
 7. A method for finding business information for a customer about subscribers to an email newsletter: for each subscriber to the email newsletter, determining subscriptions to other email newsletters; for the subscribers, determining total number of the subscriptions to the other email newsletters; for each pair of subscribers to the email newsletter, determining which of the other email newsletters the pair has in common, and how many of the other email newsletters the pair has in common as common number; for each pair of subscribers to the email newsletter, determining a connection value between the pair by dividing numerator including the common number by denominator including square root of the total number of the subscriptions to the other email newsletters of one of the pair of subscribers multiplied by square root of the total number of the subscriptions to the other email publications of the other of the pair of subscribers; and from the connection values for each pair of subscribers, determining a weightiest connection value; determining the pair of subscribers having the weightiest connection value; determining the other email newsletters the pair of subscribers having the weightiest connection value have in common; and providing the customer with the business information on the other email newsletters the pair of subscribers having the weightiest connection value have in common.
 8. The method of claim 7, wherein determining the subscriptions to the other email newsletters comprises determining the subscriptions to other public email newsletters.
 9. The method of claim 7, wherein providing the customer with the business information on the other email newsletters the pair of subscribers having the weightiest connection value have in common comprises providing the customer with a display of at least part of the one or more of the other email newsletters the pair of subscribers having the weightiest connection value have in common.
 10. In a system that stores information about email campaigners including the respective lists of email addresses for each email campaign of each email campaigner, the email newsletters for each email campaign, and whether the email newsletters are public or private, a method for providing an email campaigner with information about common public email newsletters between two email addresses on a list of email addresses of the email campaigner, comprising: receiving an identification of the list of email addresses from the email campaigner; determining number of email newsletters sent to a first email address on the list of email addresses; determining number of email newsletters sent to a second email address on the list of email addresses; comparing the email newsletters sent to the first email address with the email newsletters sent to the second email address to find public email newsletters common to both the first email address and the second email address; determining number of common public email newsletters; finding a connection value between the first email address and the second email address by using the number of email newsletters sent to the first email address, the number of email newsletters sent to the second email address, and number of the public email newsletters common to both the first email address and the second email address; and presenting the connection value to the email campaigner.
 11. The method of claim 10, further comprising: selectively displaying at least a part of each of the public email newsletters common to both the first email address and the second email address. 